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AI Superstream. MLOps.
MLOps is consistently one of the greatest challenges engineers face when creating and maintaining machine learning systems. Join expert practitioners to learn techniques and best practices for operationalizing machine learning models and explore case studies of them in action, showing you what works...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , , , , |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
[2022]
|
| Edición: | [First edition]. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 511 | 0 | |a Host, Shingai Manjengwa ; speakers include Susan Shu Chang, Olga Tsubiks, Noah Gift, Jason Bell, Isabel Zimmerman, Todd Underwood. | |
| 505 | 0 | 0 | |t MLOps from good to great / |r Susan Shu Chang |g (19:25) -- |t MLOps culture for continuous experimentation / |r Olga Tsubiks |g (27:58) -- |t What can MLOps learn from the SRE mindset? / |r Noah Gift |g (30:47) -- |t Deployment and metrics of machine learning models with Kubernetes and Prometheus / |r Jason Bell |g (32:51) -- |t Composable tools for robust MLOps deployment / |r Isabel Zimmerman |g (29:33) -- |t ML model quality as a reliability problem / |r Todd Underwood |g (29:56). |
| 520 | |a MLOps is consistently one of the greatest challenges engineers face when creating and maintaining machine learning systems. Join expert practitioners to learn techniques and best practices for operationalizing machine learning models and explore case studies of them in action, showing you what works--and what doesn't. This recording of a live event is for you because...you're a data or machine learning practitioner who puts machine learning models into production, or you're embarking on an MLOps career path, or if you want to improve your process of productionizing machine learning models by applying new techniques and best practices. | ||
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| 700 | 1 | |a Gift, Noah. |e speaker. | |
| 700 | 1 | |a Bell, Jason |c (Computer scientist), |e speaker. | |
| 700 | 1 | |a Zimmerman, Isabel. |e speaker. | |
| 700 | 1 | |a Underwood, Todd |c (Computer scientist), |e speaker. | |
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